Design of point-of-care electrochemical sensor for therapeutic drug monitoring of ofloxacin in biological fluids

Abstract

A disposable screen-printed sensor has been crafted specifically for therapeutic drug monitoring purposes, particularly for detecting ofloxacin in biological fluids. To enhance selectivity toward ofloxacin, a supramolecular calix [6] arene serves as the ionophore of choice. The sensor incorporates a graphene nanocomposite as an ion-to-electron transducer layer, which not only boosts potential stability but also mitigates potential drift. The developed ofloxacin sensor underwent rigorous characterization following IUPAC guidelines. The linearity range spans from 1 × 10^–6 to 1 × 10^–2 M, with a measured slope of 59.0 mV/decade. Impressively, it boasts a percentage recovery of 100.18 ± 1.60 and a low detection limit (LOD) of 6 × 10^–7 M. Stability assessments indicate reliable performance over an extended period of 8 weeks. The versatility of this sensor extends to various applications, including the determination of ofloxacin in pharmaceutical formulations, bulk powder, and biological fluids. Notably, it has demonstrated efficacy post-bioanalysis validation, adhering to Food and Drug Administration regulations. This advancement holds promise for personalized therapeutic drug monitoring in clinical pharmacy studies and quality control laboratories, thereby optimizing patient care at the point-of-care.

Graphical abstract

Introduction

Therapeutic drug monitoring (TDM) plays a crucial role in tailoring medical care to each patient's needs, impacting the prescription regimen significantly (Kang and Lee 2009; Teymourian et al. 2020; Hesham et al. 2024). Its primary objective is to maintain optimal concentrations of challenging medications to improve clinical outcomes across various medical scenarios (Kang and Lee 2009). Particularly for antibiotics, frequent TDM is essential to ensure adequate dosage exposure, mitigate antibiotic resistance, and minimize side effects (Osorio et al. 2021). Inadequate antibiotic concentrations can lead to decreased cure rates and foster the development of bacterial resistance (Ayukekbong et al. 2017; Gad et al. 2021; Kümmerer 2009).

TDM encompasses not only the measurement of drug concentrations in plasma samples but also extends to salivary and urinary samples (Amponsah and Pathak 2022). Utilizing alternative sample sources such as saliva offers a noninvasive collection method, potentially reducing the risks and costs associated with blood-based TDM (Braun et al. 2016; Tsubakihara et al. 1994). While blood sampling remains prevalent, it poses risks such as infection, pain, and local hematoma, particularly problematic in certain demographics like neonates and the elderly (Hutchinson et al. 2018).

Ofloxacin is a potent broad-spectrum antibiotic of the fluoroquinolone class utilized for bacterial infections (Si et al. 2018). Its chemical structure is depicted in Fig. 1. Ofloxacin functions by inhibiting DNA gyrase, topoisomerase type II and IV enzymes crucial for detaching replicated DNA, thereby impeding bacterial cell division (Hussain et al. 2016). Notably, ofloxacin stands out for its dual administration routes, being effective both orally and intravenously, a feature not common among broad-spectrum antibacterial drugs (Todd and Faulds 1991).

Fig. 1

Chemical structure of ofloxacin

Ofloxacin has demonstrated efficacy across various infections, often comparable to standard treatments (Si et al. 2018). In pediatric cases of acute uncomplicated typhoid fever, ofloxacin achieves a serum C max of approximately ~ 24 μM following intravenous injection (Bethell et al. 1996). In the context of “precision medicine,” there is a pressing need to develop sensitive and selective methods, such as point-of-care testing diagnostics (POCT), for accurately determining ofloxacin levels in biological fluids, enabling personalized dosage adjustments. Recent research suggests that monitoring ofloxacin concentrations in saliva is a valid approach, correlating well with blood levels. This method ensures that the drug concentration effectively reaches therapeutic targets, particularly in bronchial secretions (Hutchinson et al. 2018; Kumar and Gurumurthy 2004; Koizumi et al. 1994).

Existing methods for monitoring plasma ofloxacin levels typically rely on blood samples analyzed through immunoassays, high-performance liquid chromatography–mass spectrometry (HPLC–MS) (Attimarad and Alnajjar, 2013), HPLC (Attimarad and Alnajjar, 2013; Immanuel and Kumar 2001), liquid chromatography with tandem mass spectrometry (LC–MS/MS) (Meredith et al. 2012), or dispersive micro solid-phase extraction (DµSPE) (Owaid et al. 2020; Attimarad and Alnajjar, 2013; Meredith et al. 2012; Immanuel and Kumar 2001). However, these methods are laborious, time-consuming, and require fully equipped laboratories, resulting in turnaround times ranging from hours to days. Consequently, TDM of ofloxacin is infrequently conducted, providing limited data points that may not accurately reflect a patient’s metabolism and pharmacokinetics (Zeng et al. 2019; Abdul-Aziz et al. 2020). The slow and cumbersome nature of current drug measurement methods poses a significant barrier to wider TDM adoption, especially in resource-limited settings.

Electrochemical sensing methods have emerged as a prominent tool for detecting various drugs, including ofloxacin, in biological samples owing to their array of benefits: high sensitivity, selectivity, rapid detection, cost-effectiveness, ease of use, portability, and swift response. Ofloxacin has received considerable attention in the development of such methods. Specific electrochemical sensing techniques tailored for detecting ofloxacin in biological samples include voltammetric techniques (Feng et al. 2020), electrochemical impedance spectroscopy (EIS) (Hui and Ying 2017), electrochemical biosensors leveraging enzymes or antibodies for detection (Majdinasab 2017), microfluidic electrochemical devices integrating electrochemical sensors with microfluidic platforms to enhance detection capabilities (Wu et al. 2022), screen-printed electrodes (Liu et al. 2023), and nanostructured electrodes incorporating materials like carbon nanotubes, graphene, and metal nanoparticles to improve sensitivity (Solangi et al. 2022). While these methods hold promise for ofloxacin detection, achieving high specificity for ofloxacin detection in complex samples can be challenging, especially in the presence of structurally similar compounds or matrix effects, necessitating advanced signal processing or multi-parameter analysis approaches. When selecting or designing an electrochemical sensing strategy for ofloxacin detection, it is crucial to weigh these advantages and disadvantages based on specific application requirements and constraints.

Our objective of this study is to establish a platform that facilitates the measurement of plasma, urine, or salivary drug levels as easily and conveniently as existing blood glucose measurements in point-of-care settings (Dauphin-Ducharme et al. 2019). It aims at development of an electrochemical sensor, a reagent-less, single-step sensing platform for rapid, real-time measurement of drug levels in these biological fluids. Electrochemical methods offer several advantages over traditional analytical methods, including simplicity, cost-effectiveness, high sensitivity, easy miniaturization, portability, rapid response, user-friendliness, wide concentration measurement range, low power requirements, and eco-friendliness (Hassan et al. 2020; Mohamed 2016), making them a sustainable option for TDM implementation.

In this work, we fabricated solid-contact ion-selective electrode for selectively determining ofloxacin in spiked biological fluids (plasma, urine, and saliva) and pharmaceutical formulations. Firstly, screening for a selective ionophore to enhance selectivity was performed. Secondly, to enhance sensor performance, graphene nanocomposite has been introduced between the screen-printed carbon electrode and the ion-selective membrane. The effect of graphene integration on the fabricated sensor’s stability and performance was investigated by studying the aqueous layer and potential drift tests. These sensors’ figure of merit was assessed as stated by International Union of Pure and Applied Chemistry (IUPAC) guidelines (Thompson et al. 2006). Finally, the developed sensor has been utilized for determining ofloxacin in its pharmaceutical formulations and in spiked biological fluids with neither previous separation nor sample pretreatment.

Experimental

Instruments

Jenway Model 3330 Digital Ion Analyzer (Essex, UK) with Ag/AgCl with 3 M KCl double-junction reference electrode (Aldrich Chemical Co. Stein Heim, Germany).

Chemicals and materials

Pure ofloxacin powder was kindly provided from SEDICO Pharmaceutical Company, Egypt, with a purity of 100.4% ± 0.8. Ofloxacin tablets were supplied by SEDICO Pharmaceutical Company, Egypt, batch number (18,871/2008), each tablet labeled to contain 200 mg ofloxacin as active ingredient. ORNI-O™ tablets, manufactured by Acme Lite Tech-LLP, India, batch number (ALT19317), each tablet labeled to contain both 200 mg ofloxacin and 500 mg ornidazole as active pharmaceutical ingredients.

High molecular weight polyvinyl chloride (PVC), 2-nitrophenyl octyl ether (o-NPOE), potassium tetrakis(chlorophenyl)borate (K-TpCPB), calix-4-arene (CX4), tetrahydrofuran (THF), 2-hydroxypropyl β-cyclodextrin (2-HP-β-CD), and calix-6-arene (CX6) were purchased from Sigma-Aldrich (Stein Hei, Germany). (Pe)₄N Br was obtained from Merck (Darmstadt, Germany). KCl, NaOH, o-H₃PO₄ solution, xylene, and KH₂PO₄ and boric acid were purchased from Al-Nasr pharmaceutical chemical company (Cairo, Egypt). Screen-printed carbon electrodes (C-SPE) with a diameter of 3 mm were obtained from CH Instruments Inc., (Texas, USA). Graphene nanoplatelets, with 6–8 nm thickness and 5 microns width, were purchased from Strem Chemicals Inc. (New-bury port, USA).

Standard solutions

Ofloxacin stock standard solution (1 × 10^–2 M).

An accurate weight equivalent to 90.4 mg of ofloxacin was transferred to a 25-mL volumetric flask. The volume was then adjusted to achieve a final concentration of (1 × 10^–2 M) using Britton–Robinson buffer (BRB), pH 2.9.

Ofloxacin (OFL) working standard solutions

Fresh ofloxacin solutions with varying concentrations (1 × 10^–7–1 × 10^–3 M) were prepared by serial dilutions from a stock solution using a BRB pH 2.9.

Procedures

Fabricating ofloxacin sensors

Preparation of ion-selective membranes impregnated with various ionophore:

To screen for the ionophore, various sensors were prepared. The ionophore-free membrane (sensor 1a) was composed of 66.6 wt% o-NPOE, 33.17 wt% PVC, and 0.23 wt% K-TpCPB with a total weight (600 mg) was mixed and dissolved in 6.0-mL tetrahydrofuran. Sensor 1b contains CX6 as ionophore, with the membrane composed of 66.6 wt% o-NPOE, 32.54 wt% PVC, 0.23 wt% K-TpCPB, and 0.63 wt% CX6. Sensor 1c contains CX4, with the membrane composed of 66.6 wt% o-NPOE, 32.75 wt% PVC, 0.23 wt% K-TpCPB, and 0.42 wt% CX4. Sensor 1d has 2-HP-β-CD as ionophore, and the membrane composed of 66.6 wt% o-NPOE, 31.85 wt% PVC, 0.23 wt% K-TpCPB, and 1.32 wt% 2-HP-β-CD.

All ionophore-doped membranes contain K-TpCPB and the respective ionophore in a 1:2 molar ratio. K-TpCPB was used to enhance long-term stability of the sensor (Mousavi et al. 2018).

Graphene nanocomposite (GNC) preparation

As previously reported by our group (Mahmoud et al. 2020; Moaaz et al. 2021), 1.0% (w/v), a graphene nanocomposite was prepared using the solution dispersion procedure outlined by Li et al. (2014). In brief, 95.0 mg PVC was dissolved in 3.0-mL THF along with 0.2-mL plasticizer (i.e., o-NPOE). A 10.0-mg portion graphene was dispersed in 1.0-mL xylene using ultrasonication for 5 min. Subsequently, the graphene dispersion was mixed with THF solution and subjected to further ultrasonication for 10 min.

Solid-contact ion-selective sensors assembly

Fabricating control screen-printed (C-SPE/ISM) sensor 2

A 20.0 μL of the optimized ion-selective membrane was cast onto the surface of C-SPE and left to evaporate over night at room temperature.

Preparation of screen-printed/graphene nanocomposite (C-SPE/GNC/ISM) sensor 3

A 10.0 μL of GNC dispersion was applied onto C-SPE and left to evaporate over night at room temperature. The preparation steps were carried out as previously described for the fabrication of C-SPE/ISM (sensor 2).

Conditioning of solid-contact ion-selective electrodes

The fabricated C-SPE sensors were immersed for 24 h in 1 × 10^–3 M ofloxacin solution before measurements were conducted.

Evaluation of operative life, response time, and slope of the suggested sensors

The electrochemical performance of proposed sensors was evaluated according to the international union of pure and applied chemistry (IUPAC) guidelines (Thevenot et al. 1996).

Ionophore-doped membranes’ selectivity level

To study the selectivity of the ionophore toward ofloxacin and its ability to decrease the transfer energy of ofloxacin ion into the ion-selective membrane (ISM), we employed the reference ion method commonly used in potentiometry. The potential differences between various ISM potential and reference ion is measured (ΔE = E_i − E (Pe)₄N⁺) in electromotive force (emf). The reference ion chosen for this study was (Pe)₄N⁺. The response of different ionophore-doped membranes to ofloxacin and to the interferent ornidazole (co-formulated with ofloxacin in ORNI-tablets) was noted.

Aqueous layer test and signal drift recording for potential stability testing

The aqueous layer test was conducted by measuring the potential response of both C-SPE sensors (SPE sensors 2 and C-SPE 3) for 3 h. During the first hour, the sensors were immersed in 1 × 10^–3 M ofloxacin. Subsequently, for the second hour, the sensors were transferred into 1 × 10^–2 M tetrapentylammonium bromide. Finally, in the third hour, the sensors were immersed in 1 × 10^–3 M ofloxacin solution. The potential signal drift was observed by recording the emf values.

The effect of pH on the sensor performance

The effect of pH on the response sensor 3 (C-SPE/GNC/ISM(CX6)) was recorded over the pH range of 2–10. The potential measured at each pH value was recorded and plotted as function of pH.

Sensor selectivity study

The separate solutions method (SSM) as described by Zhang et al. (2000) was used to assess the extent to which an extraneous substance may interfere with the determination of ofloxacin using C-SPE/GNC/ISM(CX6), sensor 3. In the appearance of various additives and in the appearance of ornidazole (co-formulated with ofloxacin in ORNI-tablets), the potential response sensor was recorded. The potentiometric selectivity coefficient (log K_AB) was calculated according to the following equation:

$$- \log \, K_{{{\text{OFL}},{\text{ Int}}}}^{{{\text{pot}}}} = \left( {E_{1} - E_{2} /S} \right){-}\left( {1 - Z_{{{\text{OFL}}}} /Z_{{{\text{Int}}}} } \right) \, \log \, a_{{({\text{OFL}})}}$$

where E₁ is the measured potential of 1.0 × 10^–3 M of ofloxacin and E₂ is the measured potential of 1.0 × 10^–3 M of interfering ion. S is the slope of the involved sensor. Z_OFL and Z_Int are the charges of ofloxacin (Z_OFL = 1) and interfering ion, respectively, and a_(OFL) is the drug concentration in terms of activity.

Calibration of sensors

Each sensor was individually paired with double-junction reference electrode and calibrated by immersion in solutions of ofloxacin (1 × 10^–7 to 1 × 10^–2 M). The solutions were stirred using a magnetic stirrer until a constant emf was obtained. Calibration curves were then plotted between the emf recorded from the suggested sensors against the ofloxacin concentration [− log of [OFL]. Subsequently, the corresponding regression equations were calculated.

Electrochemical determination of ofloxacin in dosage forms

Ten tablets were accurately weighed and grinded into a fine powder. A weight of 0.09 g ofloxacin was transferred into a 25-mL volumetric flask, and BRB pH 2.9 was used to complete the volume. The resultant solution concentration is claimed to be 1 × 10^–2 M ofloxacin. From the prepared solution, 2.5 mL was withdrawn and transferred into a 25-mL volumetric flask and again BRB at pH 2.9 was used to complete the volume, resulting in a 1 × 10^–3 M ofloxacin solution. In the prepared solution, the screen-printed graphene nanocomposite electrode (C-SPE/GNC/ISM(CX6), sensor 3) was immersed with the Ag/AgCl double-junction reference electrode. The potentials measured from this setup were used to calculate ofloxacin corresponding concentrations from the regression equation of that sensor.

Electrochemical determination of ofloxacin in spiked human biological fluids; (plasma, urine, and saliva)

Preparation of calibrator samples

Human plasma was obtained from holding company for biological products and vaccines (Vacsera) in Cairo, Egypt, urine, and saliva sourced from six different origins. All samples were collected and used in their original state without deprotonation or purification.

Linearities

Calculated aliquots of stock standard solution were transferred to a 10-mL volumetric flask and diluted with borate buffer. The final samples were prepared by mixing 1 ML of each concentrations with 1 mL of biological fluids to obtain the concentration rang of 1 × 10 − 7—1 × 10 − 2. The procedure followed was as described in “Calibration of Sensors” section. To construct the calibration curves, the regression was computed and bioanalysis validation was performed.

Preparation of quality control samples

Quality control (QC) samples consisting of low (QCL), medium (QCM), and high (QCH) concentrations were used. QCL was set at three times the lower limit of quantification (LLOQ). The QCM ranged from 30 to 50% and QCH was 70% of the highest concentration in the range. Into three 10-mL volumetric flasks, 1 mL of ofloxacin-free human biological fluids (plasma, urine, and saliva) was separately introduced in each flask. Subsequently, 1 mL of ofloxacin standard solutions (ranging from 1 × 10^–4 to 1 × 10^–2 M) was added in each flask. The volumes were completed using BRB pH 2.9 to obtain a final concentration of 1 × 10^–5, 1 × 10^–4 and 1 × 10^–3 M of OFL in each sample. The screen-printed graphene nanocomposite electrode (C-SPE/GNC/ISM (CX6), sensor 3) was used to estimate the ofloxacin concentration in the samples without pretreatment. Ofloxacin concentrations were calculated from the corresponding regression equation.

Results and discussion

Frequent therapeutic drug monitoring (TDM) is essential to ensure that adequate optimal concentrations of the drugs, particularly antibiotics, are maintained throughout the course of treatment. Current methods for monitoring plasma ofloxacin levels, especially in the presence of structurally similar compounds or matrix effects, are time-consuming and demand fully equipped laboratories, resulting in turnaround times ranging from hours to days. Electrochemical sensing methods have emerged as a prominent tool for detecting various drugs, including ofloxacin, in biological samples due to their array of benefits: high sensitivity, selectivity, rapid detection, cost-effectiveness, ease of use, portability, and swift response.

Potentiometric ion-selective electrodes (ISEs) have found extensive application across ecological (De Marco et al. 2007), medical, and biological fields (Ding and Qin 2020; Oesch et al. 1986). These electrodes facilitate the determination of target ion activity in sample solutions by measuring electromotive force at the electrode/sample interface against a reference electrode (Mahmoud et al. 2020). While conventional liquid-contact ISEs were the initial platform, their drawbacks, such as solution evaporation and short lifespan, prompted the development of solid-state ISEs (Burnett et al. 2000; Rius-Ruiz et al. 2011; Wring et al. 1990). Solid-contact ISEs offer advantages such as ease of fabrication, miniaturization, and mass production (Fares et al. 2022). However, they are susceptible to potential drift over time (Ayish et al. 2022; Lyu et al. 2020). To address these issues, hydrophobic ion-to-electron transducer layers, typically positioned between the electrode surface and ion-sensing membrane, have been proposed. Conducting polymers with high oxidation–reduction capacity, such as polyaniline and polypyrrole, have been utilized for this purpose (Vanamo and Bobacka 2014), demonstrating improvements in detection limits and potential drift reduction. However, these polymers are sensitive to factors like light, oxygen, CO₂, and sample pH (Li et al. 2012).

Graphene, being a remarkable carbon allotrope, possesses numerous merits that render it highly attractive for various applications, including biosensing. Graphene-based materials have received significant attention in biosensing applications due to their versatility and potential, showcasing remarkable capabilities in enhancing sensitivity, selectivity, and reliability for the detection of biomolecules. As a single-layer carbon allotrope arranged in a 2D lattice structure, it has emerged as a promising material for enhancing the stability and signal of screen-printed electrodes (SPEs) while eliminating unwanted aqueous layers (Hassan et al. 2022; Sharma et al. 2014; Sharma et al. 2013). By integrating graphene into SPEs, improved electrode stability and signal integrity can be achieved, contributing to the advancement of potentiometric ISEs for various applications.

In recent studies, innovative approaches have been explored for the bioanalysis of antibiotics and other biomolecules using advanced materials and techniques. For instance, a photoelectrochemical bioanalysis method based on branched hybridization chain reaction, utilizing rGO–Bi₂WO₆–Au hybrids, and gold nanoclusters-functionalized MnO₂ nanosheets with target-induced etching reaction were developed for the quantitative or qualitative screening of antibiotic residues (Zeng et al. 2018, 2019). Additionally, a signal-on photoelectrochemical sensing system employing reduced graphene oxide/BiFeO₃ nanohybrids was developed for the detection of prostate-specific antigen (Zhou et al. 2018). Like the previous methods, this approach sounds complex and time-consuming, requiring precise control over experimental conditions and optimization of assay parameters. The presence of reduced graphene oxide (rGO), bismuth tungstate (Bi₂WO₆), and gold (Au) or rGO and BiFeO₃ suggests a multi-step synthesis process to fabricate the sensing platform, necessitating fully equipped laboratories and considerable time.

Building on these advancements, our work focused on fabricating a solid-contact ion-selective electrode tailored for selectively determining ofloxacin in spiked biological fluids (plasma, urine, and saliva) as well as pharmaceutical formulations. The electrochemical monitoring of ofloxacin depends on the selective binding of the compound to a recognition element immobilized on an electrode surface. Subsequently, this binding event is transduced into a measurable electrochemical signal for quantification. This approach presents several advantages, including high sensitivity, selectivity, and rapid detection, rendering it suitable for diverse applications in pharmaceutical analysis, environmental monitoring, and clinical diagnostics. Initially, we conducted screening to identify a selective ionophore to enhance the sensor’s specificity. Subsequently, to further improve sensor performance, we introduced a graphene nanocomposite between the screen-printed carbon electrode and the ion-selective membrane. The impact of graphene integration on the sensor’s stability and performance was thoroughly investigated through aqueous layer and potential drift tests. The sensors’ figure of merit was assessed in accordance with IUPAC guidelines.

Finally, the developed sensor was applied to the determination of ofloxacin in both pharmaceutical formulations and spiked biological fluids without the need for prior separation or sample pretreatment. This approach represents a promising step toward efficient and convenient ofloxacin monitoring in various clinical and pharmaceutical settings.

Sensing mechanism of ion-selective electrodes (ISEs)

In the fabrication of ion-selective electrodes (ISEs), a high molecular weight PVC matrix serves as a crucial support of the ISEs. Plasticization is essential in this process with specific considerations for the selection of mediator (Ragab et al. 2015). The ratio of the membrane constituents and the choice of plasticizer significantly impact the response of PVC ISEs, as demonstrated by Gupta et al. (2007). Plasticizers play a vital role in adjusting membrane permittivity to achieve maximum sensitivity and selectivity (Gupta et al. 2006). It is imperative to adjust he quantity of plasticizer to minimize membrane electrical unevenness and prevent component leakage into the sample solution as emphasized by Feng and Huang (1997). Several plasticizers including dioctyl phthalate (DOP), dioctyl sebacate (DOS), and o-NPOE have demonstrated optimum results and have thus been selected for further experiments. Moreover, the type of ion exchanger is another key factor in ISEs optimization and fabrication. Ion exchangers are hydrophobic ionic sites that enhance the process of exchanging the ions at the membrane/sample interface, thereby reducing the resistance of ion-selective membrane. By providing abundant ionic sites within the membrane matrix, they contribute significantly to its performance as discussed by Melnikov et al. (2020). These factors collectively play a pivotal role in the successful optimization and fabrication of ISEs for various applications.

Screening ionophores selectivity toward ofloxacin

Supramolecular macrocycles such as cyclodextrins, calixarenes, resorcinarene, cucurbiturils, and pillarenes have been extensively investigated in target drug delivery and analytical chemistry, as well as in optical sensors and water pollution treatment (Hu et al. 2020). Calixarenes, in particular, are widely studied in the realm of supramolecular hosts and molecular recognition (Han et al. 2014). Calixarenes possess basket-shaped electron-rich aromatic cavities of various sizes that can significantly influence both binding strength and selectivity of the host receptors toward the target analyte through cation-π interactions (Georghiou et al. 2005).

Initially, various ISM sensors labeled as Ia, Ib, Ic, and Id were prepared for the screening of the optimum ionophore and ISM cocktail. Selective ionophore screening was made by investigating the effects of three commercially available ionophores on selectivity.

A recent study has investigated the complexation and utilization of calixarene derivative as a drug carrier system for ofloxacin to enhance its bioavailability (Migliore et al. 2021). Therefore, calixarenes 4, 6, and 2-HP-β-CD were incorporated into the sensing membrane as potential ofloxacin candidate ionophores. The potentiometric technique was used to determine the binding constant among the host ion and the guest macromolecule. As reported in the literature, reference ion methods are used to assess the binding degree for organic ions (Ceresa and Pretsch 1999). In this method, a large aquaphobic ion is employed as a reference ion which unable to fit into the supramolecular cavity. Subsequently, the potential differences (ΔE = E_i − E (Pe)₄N⁺) (Mahmoud et al. 2020) among the emf values of the dissimilar ISMs (ionophore-free, or doped with 2-HP-β-CD, CX6, or CX4) in response to ofloxacin and reference ion were calculated (Fig. 2). The CX6-doped membrane exhibited the minimum ΔE (402.1 mV) for ofloxacin compared to the ionophore-free membrane (438 mV). In contrast, the ΔE recorded was 417.2 mV and 423.4 mV for the CX4 and 2-HP-β-CD doped membranes, respectively. The results shown in Fig. 2 support that CX6 has the maximum affinity for ofloxacin which is consistent with the literature. Therefore, Calix [6] arene was adopted as ionophore in the determination of ofloxacin potentiometrically and was used to fabricate two screen-printed electrodes (SPE). The first C-SPE was a control sensor drop-casted only with the CX6-doped membrane (sensor 2) and the second sensor was covered with a transducer layer of nanocomposite graphene dispersion, followed by the ISM (sensor 3).

Fig. 2

Potential response of ionophore free ISE (sensor Ia), CX4-based ISE (sensor Ic), CX6-based ISE (sensor Ib) and 2-HP-β-CD based ISE (sensor Id) to ofloxacin solutions of 1 × 10^–3 M concentration and after subtraction of the emf of theses ISEs to (1 × 10^–3 M (Pe)₄N⁺)

Potentiometric sensors using CX6-doped membrane

Two SC-ISEs were fabricated and used to determine ofloxacin using a sensing membrane called CX6-doped ion-selective membrane. SP sensor 2 consisted solely of the CX6 membrane without any transducer layer. Sensor 3, denoted as C-SPE/GNC/ISM(CX6), was initially modified with a transducer layer of graphene nanocomposite, followed by the addition of that the CX6 ISM layer. The signal drift was assessed by monitoring the values of emf over time.

In Fig. 3A, C-SPE/GNC/ISM(CX6), sensor 3, showed stability enhancement with only a signal drift of approximately ~ 0.8 mV/h, in contrast to C-SPE/ISM(CX6) sensor 3, which demonstrated a signal drift of around 12 mV/h (Fig. 3B). These results confirm that the incorporation of graphene nanocomposite enhances electrode stability and reduces signal drift. This enhancement is likely attributed to the hydrophobic nature of graphene, which impedes the development of an aqueous layer between the PVC membrane and the carbon electrode. To further asses this theory, aqueous layer test was conducted.

Fig. 3

(A) Signal drift for C-SPE/ISM(CX6), sensor 2 and C-SPE/GNC/ISM(CX6), sensor 3. Readings were recorded in 1 × 10^–3 M ofloxacin. (B) Signal drift for C-SPE/GNC/ISM(CX6), sensor 3. Readings were recorded in 1 × 10^–3 and 1 × 10^–2 M ofloxacin

Calibration of sensors and response time

Table 1 presents the results obtained for the response characteristics over an 8-week period for the proposed sensors. The characteristic calibration graphs are illustrated in Fig. 4. The slope is calculated from the linear portion of the calibration curve. The slopes of the solid-contact electrodes’ calibration graphs are 53.3 and 59.0 mV/decade for the C-SPE/ISM(CX6), sensor 2 and the C-SPE/GNC/ISM(CX6), sensor 3, respectively. The time required for the sensors to reach stable potentiometric readings after increasing the drug concentration by 10 times was found to be 8 s for the C-SPE/ISM(CX6), sensor 2 and close to 2 s for the C-SPE/GNC/ISM(CX6), sensor 3. The C-SPE/ISM(CX6), sensor 2, remains stable over four weeks, while the C-SPE/GNC/ISM(CX6), sensor 3, remains stable and accurate for eight weeks.

Table 1 Response characteristics of the sensors studied for the determination of ofloxacin (OFL)

Fig. 4

Potential profile in mV/- Log ofloxacin molar concentration using C-SPE/ISM(CX6), sensor 2 [1 × 10^–7–1 × 10^–2 M] and C-SPE/GNC/ISM(CX6), sensor 3 [1 × 10^–7–1 × 10^–2 M]

Aqueous layer test and signal drift detection for the SPEs

In the aqueous layer test (Hambly et al. 2020), initially, potential readings were recorded from a 1 × 10^–3 M ofloxacin solution. Subsequently, measurements were taken upon introducing a solution of a cationic hydrophobic compound (tetrapentylammonium bromide) at a concentration of 1 × 10^–3 M. An increase in potential was observed. This increase can be attributed to the replacement of ofloxacin with tetrapentylammonium bromide in the ISM. The final step involved replacing the test solution with the initially used 1 × 10^–3 M ofloxacin solution. Interestingly, there was nearly no drift in potential when using C-SPE/GNC/ISM(CX6), sensor 3, compared to C-SPE/ISM(CX6), sensor 2, which exhibited significant potential drift (Fig. 5). This suggests that a GNC layer in sensor 3 prevents water layer formation due to its hydrophobic film effect.

Fig. 5

Water layer test for C-SPE/ISM(CX6), sensor 2 and C-SPE/GNC/ISM(CX6), sensor 3. Readings were done in 1 × 10^–3 M ofloxacin, 1 × 10^–3 M tetrapentylammonium bromide and then 1 × 10^–3 M ofloxacin

Therefore, the selected electrode for all the measurements was the C-SPE/GNC/ISM(CX6), sensor 3. Consequently, it was applied for determination of ofloxacin in both dosage forms and spiked human fluids.

Effect of pH on sensor characteristics

The pH effect on the response of C-SPE/GNC/ISM(CX6), sensor 3, was investigated (Fig. 6) using 1 × 10^–3 and 1 × 10^–4 M OFL across a pH range of 2.0–10.0. It is clear that the sensor’s potential response remains quite stable within the pH range 2.0–5.0 where the ofloxacin is completely ionized and can be effectively detected by the ISM.

Fig. 6

pH effect on the response of C-SPE/GNC/ISM(CX6), sensor 3 using 1 × 10^–3 and 1 × 10^–4 M ofloxacin

Selectivity of the sensors

The response of C-SPE/GNC/ISM(CX6), sensor 3, in the presence of ornidazole (co-formulated drug with ofloxacin in ORNI-tablets), excipients of tablets, and both inorganic and organic related ingredients, was evaluated using the separate solutions method. The selectivity coefficients calculated from obtained results confirm a high selectivity toward ofloxacin from the proposed sensor, with minimal interference from the studied interfering substances, as shown in Table 2 and Fig. 7A, B.

Table 2 Potentiometric selectivity coefficients of C-SPE/GNC/ISM(CX6), sensor 3 using separate solution method (SSM)

Fig. 7

(A, B) Calibration plots obtained for ofloxacin, potentially interfering ions using C-SPE/GNC/ISM(CX6), sensor 3, showing a Nernstian response toward ofloxacin. This response is attributed to the differences in ionic size and lipophilicity when compared to the studied drug. Measurements were performed in phosphate buffer (pH = 2.9)

Electrochemical determination of ofloxacin in spiked biological fluids

The sensor was utilized to detect ofloxacin in various biological fluids. All samples were collected and used in their original state without deprotonation or purification. The sampling collection of biological fluids, construction of linearity, calculation of lower limit of quantification (LLOQ), and validation parameters were conducted in accordance with relevant FDA (FDA 2018) guidelines to ensure compliance and accuracy in the analysis process.

Bio-analysis validation (linearity, lower limit of quantification (LLOQ))

For linearity and determination of the LLOQ, a calibration curve of the drug in biological fluids was constructed. Triplicates of three concentrations were analyzed using the developed method and the obtained potential was plotted against the corresponding concentration (Fig. 8). LLOQ represents the lowest concentration that can be quantified based on the calibration curve. The acceptable range for accuracy is 80–120%, or %R is ± 15%. For precision, the percentage relative standard deviation (% RSD) should not exceed 15% except for the LLOQ, where it can be ± 20%. (Table 3).

Fig. 8

Potential profile in mV/- Log ofloxacin molar concentration using C-SPE/ISM(CX6), sensor 2 [1 × 10^–7–1 × 10^–2 M] and C-SPE/GNC/ISM(CX6), sensor 3 [1 × 10^–7–1 × 10^–2 M] in biological fluids

Table 3 Determination of ofloxacin in quality control spiked biological fluid samples (plasma, urine, and saliva) using C-SPE/GNC/ISM(CX6), sensor 3

In evaluating accuracy and precision, triplicates of each quality control (QC) sample were utilized.

• Accuracy defined as the degree of closeness of the results to the true value. It was assessed within run and between run using the percentage recovery (%R).

  $$\% R = \left( {{\text{Found}}\;{\text{concentration}}/{\text{Theoretical}}\;{\text{concentration}}} \right) \times 100.$$

• Precision measures the closeness of the results to each other within-run and between-run precision were evaluated as:

  $$\% {\text{RSD}} = {\text{SD}}/{\text{Mean}} \times \, 100$$

• Selectivity is crucial for ensuring the method's ability to accurately analyze and quantify drugs without interference from substances present in the biological matrix. To evaluate selectivity, blank samples from six different sources are used, with the requirement that the response of interfering substances should not exceed 20% of the response of the analytes at the LLOQ level.

Preparation of quality control samples

Quality control samples include low (QCL), which is three times the LLOQ, medium (QCM), which is 30–50% of the highest concentration in the range, and high (QCH), which is 70% of the highest concentration in the range. The quality control samples were prepared by the same procedure as the calibrators samples. Spiked samples were measured using the method, and concentrations were calculated using the corresponding regression equation. The detection of ofloxacin in saliva and urine is considered a noninvasive alternative to blood tests. The summarized results in Table 3 demonstrate the promising capabilities of the C-SPE/GNC/ISM(CX6) sensor 3 for measuring ofloxacin in biological fluids. These results highlight its potential for future clinical and therapeutic drug monitoring (TDM) studies.

Electrochemical determination of OFL in pharmaceutical formulation

Using the C-SPE/GNC/ISM(CX6), sensor 3, the concentration of ofloxacin in tablets was determined. The mean of three determinations showed precise and accurate recoveries of 100.2% ± 1.6 for ofloxacin in single form and 100.3% ± 1.4 for ofloxacin in binary form. This demonstrates the sensor’s ability for the detection of ofloxacin in pharmaceutical dosage forms without the need for a pretreatment procedures or extraction processes, and without the interference of the co-formulated drug ornidazole. It is noteworthy that our sensor was compared with the potentiometric method in the US pharmacopeia, as presented in Table 4.

Table 4 Statistical analysis of the results obtained by the proposed method and the official method for determining ofloxacin in pure powder form

The results obtained from C-SPE/GNC/ISM(CX6), sensor 3, were compared to the results obtained using the official potentiometric method to determine the ofloxacin pure sample. No significant difference was found in the results concerning precision and accuracy (Table 4).

Conclusion

In this study, we developed an ion-selective electrode (ISE) based on a solid-contact screen-printed electrode for the detection of ofloxacin in biological fluids for therapeutic drug monitoring and its determination in pharmaceutical formulations. We incorporated a “Nanocomposite Graphene” interlayer as a solid-contact ion-to-electron transducer. The integration of graphene nanocomposite led to improvements in both potential stability and minimized signal drifting, while also reducing the formation of an aqueous layer at the interfacial boundaries between the ion-sensing membrane and carbon screen-printed electrode. Consequently, this enhancement resulted in significant sensor stability compared to control ISEs lacking the transducer. The careful selection of the ionophore CX6 played a pivotal role in improving the selective sensing of ofloxacin with appropriate precision and accuracy. Overall, our work demonstrates the effectiveness of utilizing solid-contact screen-printed electrodes with graphene nanocomposite interlayers for enhanced stability and selective detection of ofloxacin, paving the way for its application in therapeutic drug monitoring and pharmaceutical quality control. The proposed screen-printed solid-contact potentiometric sensor was characterized according to IUPAC guidelines, revealing a slope of 59.0 mV/decade. It exhibited a linear range spanning from 1 × 10^–6 to 1 × 10^–2 M, with a limit of detection (LOD) of 6 × 10^–7 M. The fabricated ofloxacin sensor thus offers a valuable tool for its detection using a selective, sensitive, and disposable potentiometric strip, making it suitable for a range of applications, including the development of selective, sensitive, and disposable potentiometric strips. Manufactured ofloxacin sensors represent a promising tool for everyday sensing applications, eliminating the need for multiple pretreatment processes, hazardous solvents, or costly equipment. This technique is nondestructive and does not consume the analyte during analysis. Moreover, it offers non-contaminating results with a short response time, typically in seconds to minutes. Importantly, the method remains unaffected by sample turbidity or color. Compared to liquid sensors, the setup of ofloxacin sensors is straightforward, making them easy to operate and apply. They offer stability, sustainability, and economic benefits, being eco-friendly with no requirement for solvents or expensive materials. These characteristics collectively make ofloxacin sensors a practical and efficient choice for various sensing applications.